Solving real-world problems with joy for science
Mathematics as a language
Spoken languages are from nature ambiguous. Mathematics is by contrast extremely clear and exact. Preceding solution with mathematical interpretation can so truly help with understanding the problem’s essence.
The best algorithms and advanced methods are useless unless we have experts’ knowledge in a given field. Hence, close collaboration with our clients and a wide variety of external experts helps us to stay on top of the things.
As uncertainty has major influence on our behaviour we want to measure it precisely. The best tool for it are Bayesian methods. Only this approach enable us to combine our existing knowledge with available data and make optimal decisions.
Data and Machine Learning
Human minds are unbelievably efficient machines. Yet we are not able to process huge amounts of all the available data and find their hidden patterns. Fortunately, this is exactly where the latest machine learning algorithms excel.
In Abradatas, coming up with working and elegant ideas is the most rewarding experience.
Natural language processing
AUTOMATIC BESS POWER MANAGEMENT
It is hard to manage power in big Battery Energy Storage System (BESS) and use it for instance for peak shaving. One has to be aware of the weather, development of electricity prices and state of the transmission grid.
Using advanced Bayesian forecasting methods (AI) based on information about the grid, weather and prices combined with smart decision making would allow us to automatically manage power in BESS, maximizing the revenue of the energy trader/user of BESS.
The educational system in the Czech Republic hasn’t really changed much for a long time. Thanks to old practises students are provided with little motivation to learn and schools still have very few means to teach effectively.
Education depends mostly on the teachers who have nor incentives nor the time to collect feedback from students. Therefore they have only small awareness of what suits their students the best.
In cooperation with experts, we designed a questionnaire for students, then gathered answers from schools and analyze them. Finally, we provide schools with data and interactively present the results to the principal, teachers and students on Evaluace výuky web app.
One of the important measures of yield in experimental agriculture is so-called TGW (Weight of Thousand Grains – HTS in Czech ). Manual counting is expensive, time-consuming and imprecise, but still widely used.
Using computer vision approach allows us to compute not only TGW but also other features of grain – height, width, grain damage. It is also significantly faster.
Trading Assistance for Solar Global Energy
We designed an algorithm and created a tool for the prediction of solar energy production. We also implemented a Bayesian decision-making system to support traders’ decisions.
Cheaper solutions for autonomous car parks
We developed an algorithm based on Convolutional Neural Networks
that counts arriving and departing cars.
Aktuálně probíhající epidemie koronaviru je dosud největší výzvou naší generace. Lidé zodpovědní za rozhodování na všech úrovních, od městské samosprávy po vládu, jsou povinni dělat
František Smolka is a long-time Czech business leader. He has gathered a wealth of experience he is now trying to hand over to Abradatas and find a way for applied mathematics into the industry. By doing so, he returns to his youthful loves – mathematics and IT.
Jakub Dostál is a man with luck for mentors. Ignited for mathematics, he works at the Palacký University and slowly catches up with the world of business. He currently undertakes the challenge to translate the language of science into the language of the private sector. As a student, he also took part in many international scientific competitions.
Tomáš Fürst is an applied mathematician who teaches at the Palacký University. He believes that mathematics is the language of natural sciences: he focuses on mathematical modelling of diverse natural phenomena and processes, processing of all kinds of data and employing the correct, i.e. Bayesian inference.